Prediction of the pre-morbid 3D anatomy of the proximal humerus based on statistical shape modelling

Poltaretskyi, Sergii; Chaoui, Jean; Mayya, Mohammad; Hamitouche, Chafiaâ; Bercik, Michael J.; Boileau, Pascal; Walch, Gilles

doi:10.1302/0301-620x.99b7.bjj-2017-0014

Cited by 43 publications

(37 citation statements)

References 31 publications

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“…Recent studies by Poltaretskyi et al 4 and our group 5 are closely related to the present work. In those studies, another approach was presented for the generation of a 3D reconstruction template: use of a statistical shape model (SSM).…”

Section: Discussionsupporting

confidence: 88%

“…The approximation of the proximal humeral anatomy with the bilateral registration of the bicipital groove seems to be more accurate than the SSM. The mean p-HCR error around the y axis using the groove-75-85 segment was 2.1°± 1.6°, while the corresponding error in retrotorsion with the SSM of Poltaretskyi et al 4 was 3.8°± 2.9°. The 3D p-HCR in the present study using the groove-75-85 segment was 2.8°± 1.5°, while the error of the SSM with the distal-85 segment 5 was 3.8°± 1.9°.…”

Section: Discussionmentioning

confidence: 77%

“…C omputer-assisted methods have become increasingly important for the restoration of the premorbid anatomy of the proximal part of the humerus, as they support the surgeon in achieving this goal. Three-dimensional (3D) preoperative planning and intraoperative navigations techniques have been, thereby, proposed for proximal humeral fractures [1][2][3] and corrective osteotomies of the proximal part of the humerus [4][5][6] as well as for shoulder replacement surgeries 4,5,[7][8][9][10][11] .…”

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confidence: 99%

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A Novel Method for the Approximation of Humeral Head Retrotorsion Based on Three-Dimensional Registration of the Bicipital Groove

Vlachopoulos

Carrillo

Dünner

et al. 2018

The Journal of Bone and Joint Surgery

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Section: Discussionsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 77%

mentioning

confidence: 99%

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A Novel Method for the Approximation of Humeral Head Retrotorsion Based on Three-Dimensional Registration of the Bicipital Groove

Vlachopoulos

Carrillo

Dünner

et al. 2018

The Journal of Bone and Joint Surgery

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“…SSM has been used for shape reconstructions from partial information [34,35]. The SSM was fitted on the known part of the shape and, thus, the missing part of the shape was reconstructed according to the instance of the model.…”

Section: ) Posterior Principal Component Analysismentioning

confidence: 99%

Statistical Shape Model to Generate a Planning Library for Cervical Adaptive Radiotherapy

Rigaud

Simon

Gobeli

et al. 2019

IEEE Trans. Med. Imaging

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External beam radiotherapy is extensively used to treat cervical carcinomas. A single planning CT scan enables the calculation of the dose distribution. The treatment is delivered over 5 weeks. Large per-treatment anatomical variations may hamper the dose delivery, with the potential of an organs at risk (OAR) overdose and a tumor underdose. To anticipate these deformations, a recent approach proposed three planning CTs with variable bladder volumes, which had the limitation of not covering all per-treatment anatomical variations. An original patient-specific population-based library has been proposed. It consisted of generating two representative anatomies, in addition to the standard planning CT anatomy. First, the cervix and bladder meshes of a population of 20 patients (314 images) were registered to an anatomical template, using a deformable mesh registration. An iterative point-matching algorithm was developed based on local shape context (histogram of polar or cylindrical coordinates and geodesic distance to the base) and on a topology constraint filter. Second, a standard principal component analysis (PCA) model of the cervix and bladder was generated to extract the dominant deformation modes. Finally, specific deformations were obtained using posterior PCA models, with a constraint representing the top of the uterus deformation. For a new patient, the cervix-uterus and bladder were registered to the template, and the patient's modeled planning library was built according to the model deformations. This method was applied following a leave-one-patient-out cross-validation. The performances of the modeled library were compared to those of the three-CT-based library and showing an improvement in both target coverage and OAR sparing.

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“…21,22 Around the glenohumeral joint, SSM has mainly been used to approximate native anatomy for anatomic structures with bony defects. [23][24][25] However, SSM is an ideal tool to objectively quantify shape variability within a given set of samples, without idealizing the underlying anatomy. 21 Therefore, the goal of this study was to use SSM to identify the hierarchy of anatomic variance of the articular and periarticular anatomy of the scapula, and to quantify shape variation of the periarticular anatomy of the scapula in relation to the glenoid in nonpathologic shoulders.…”

mentioning

confidence: 99%

Thinking outside the glenohumeral box: Hierarchical shape variation of the periarticular anatomy of the scapula using statistical shape modeling

Jacxsens

Elhabian

Brady

et al. 2020

Journal Orthopaedic Research

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Variation in the shape of the glenoid and periarticular anatomy of the scapula has been associated with shoulder pathology. The goal of this study was to identify the modes of shape variation of periarticular scapular anatomy in relation to the glenoid in nonpathologic shoulders. Computed tomography scans of 31 cadaveric scapulae, verified to be free of pathology, were three‐dimensionally reconstructed. Statistical shape modeling and principal component analysis identified the modes of shape variation across the population. Corresponding linear and angular measurements quantified the morphometric variance identified by the modes. Linear measures were normalized to the radius of the inferior glenoid to account for differences in the scaling of the bones. Five modes captured 89.7% of total shape variation of the glenoid and periarticular anatomy. Apart from size differences (mode 1: 33.0%), acromial anatomy accounted for the largest variation (mode 2: 32.0%). Further modes described variation in glenoid inclination (mode 3: 11.8%), coracoid orientation and size (mode 4: 9.0%), and variation in coracoacromial (CA) morphology (mode 5: 3.1%). The average scapula had a mean acromial tilt of 49 ± 7°, scapular spine angle of 61 ± 6°, the glenoid inclination of 84 ± 4°, coracoid deviation angle of 26 ± 4°, coracoid length of 3.7 ± 0.3 glenoid radii, and a CA base length of 5.6 ± 0.5 radii. In this study, the identified shape modes explain almost all of the variance in scapular anatomy. The acromion exhibited the highest variance of all periarticular anatomic structures of the scapula in relation to the glenoid, which may play a role in many shoulder pathologies.

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Prediction of the pre-morbid 3D anatomy of the proximal humerus based on statistical shape modelling

Cited by 43 publications

References 31 publications

A Novel Method for the Approximation of Humeral Head Retrotorsion Based on Three-Dimensional Registration of the Bicipital Groove

A Novel Method for the Approximation of Humeral Head Retrotorsion Based on Three-Dimensional Registration of the Bicipital Groove

Statistical Shape Model to Generate a Planning Library for Cervical Adaptive Radiotherapy

Thinking outside the glenohumeral box: Hierarchical shape variation of the periarticular anatomy of the scapula using statistical shape modeling

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